Active shape models—their training and application
Computer Vision and Image Understanding
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Osteoporosis is a systemic skeletal disease, which is characterized by low bone mass and micro-architectural deterioration of bone tissue, leading to bone fragility. Finding an effective method for prevention and early diagnosis of the disease is very important. Several parameters, including broadband ultrasound attenuation (BUA), speed of sound (SOS), and stiffness index (STI), have been used to measure the characteristics of bone tissues. In this paper, we proposed a method, namely modified contour deformable model (MCDM), bases on the active contour model (ACM) and active shape model (ASM) for automatically detecting the calcaneus contour from quantitative ultrasound (QUS) parametric images. The results show that the difference between the contours detected by the MCDM and the true boundary for the phantom is less than one pixel. By comparing the phantom ROIs, significant relationship was found between contour mean and bone mineral density (BMD) with R=0.99. The influence of selecting different ROI diameters (12, 14, 16 and 18 mm) and different region-selecting methods, including fixed region (ROIfix), automatic circular region (ROIcir) and calcaneal contour region (ROIanat), were evaluated for testing human subjects. Measurements with large ROI diameters, especially using fixed region, result in high position errors (10-45%). The precision errors of the measured ultrasonic parameters for ROIanat are smaller than ROIfix and ROIcir. In conclusion, ROIanat provides more accurate measurement of ultrasonic parameters for the evaluation of osteoporosis and is useful for clinical application.